Related papers: TCP Injections for Fun and Clogging
Modern processors use branch prediction and speculative execution to maximize performance. For example, if the destination of a branch depends on a memory value that is in the process of being read, CPUs will try guess the destination and…
Recent works have demonstrated that deep learning models are vulnerable to backdoor poisoning attacks, where these attacks instill spurious correlations to external trigger patterns or objects (e.g., stickers, sunglasses, etc.). We find…
Multi-targeted adversarial attacks aim to mislead classifiers toward specific target classes using a single perturbation generator with a conditional input specifying the desired target class. Existing methods face two key limitations: (1)…
In this paper, we propose a new method for detecting unauthorized network intrusions, based on a traffic flow model and Cisco NetFlow protocol application. The method developed allows us not only to detect the most common types of network…
Cache randomization has recently been revived as a promising defense against conflict-based cache side-channel attacks. As two of the latest implementations, CEASER-S and ScatterCache both claim to thwart conflict-based cache side-channel…
The purpose of this paper is to do a general survey on the existing communication modes inside a smart grid, the existing security loopholes and their countermeasures. Then we suggest a detailed countermeasure, building upon the Jigsaw…
Malware abuses TLS to encrypt its malicious traffic, preventing examination by content signatures and deep packet inspection. Network detection of malicious TLS flows is an important, but challenging, problem. Prior works have proposed…
This paper proposes a simple yet effective jailbreak attack named FlipAttack against black-box LLMs. First, from the autoregressive nature, we reveal that LLMs tend to understand the text from left to right and find that they struggle to…
Recent studies have shown that LLMs are vulnerable to denial-of-service (DoS) attacks, where adversarial inputs like spelling errors or non-semantic prompts trigger endless outputs without generating an [EOS] token. These attacks can…
In this paper we investigate the feasibility of denial-of-service (DoS) attacks on shared caches in multicore platforms. With carefully engineered attacker tasks, we are able to cause more than 300X execution time increases on a victim task…
Predicitions made by neural networks can be fraudulently altered by so-called poisoning attacks. A special case are backdoor poisoning attacks. We study suitable detection methods and introduce a new method called Heatmap Clustering. There,…
Control flow integrity (CFI) has received significant attention in the community to combat control hijacking attacks in the presence of memory corruption vulnerabilities. The challenges in creating a practical CFI has resulted in the…
Large Reasoning Models (LRMs) have demonstrated promising performance in complex tasks. However, the resource-consuming reasoning processes may be exploited by attackers to maliciously occupy the resources of the servers, leading to a…
Cryptojacking is the permissionless use of a target device to covertly mine cryptocurrencies. With cryptojacking, attackers use malicious JavaScript codes to force web browsers into solving proof-of-work puzzles, thus making money by…
We introduce the Context Compliance Attack (CCA), a novel, optimization-free method for bypassing AI safety mechanisms. Unlike current approaches -- which rely on complex prompt engineering and computationally intensive optimization -- CCA…
Negative-Bias Temperature Instability is a dominant aging mechanism in nanoscale CMOS circuits such as microprocessors. With this aging mechanism, the rate of device aging is dependent not only on overall operating conditions, such as heat,…
Practical attacks that exploit speculative execution can leak confidential information via microarchitectural side channels. The recently-demonstrated Spectre attacks leverage speculative loads which circumvent access checks to read…
The financial industry relies on deep learning models for making important decisions. This adoption brings new danger, as deep black-box models are known to be vulnerable to adversarial attacks. In computer vision, one can shape the output…
Because of the open access nature of wireless communications, wireless networks can suffer from malicious activity, such as jamming attacks, aimed at undermining the network's ability to sustain communication links and acceptable…
The arm race between hardware security engineers and side-channel researchers has become more competitive with more sophisticated attacks and defenses in the last decade. While modern hardware features improve the system performance…